code: def test_squareform_isfc():
      # Set parameters for toy time series data
      n_subjects = 20
      n_TRs = 60
      n_voxels = 30
      random_state = 42
  
      logger.info("Testing ISC options")
  
      data = simulated_timeseries(
          n_subjects,
          n_TRs,
          n_voxels=n_voxels,
          data_type="array",
          random_state=random_state,
      )
  
      # Generate square redundant ISFCs
      isfcs_r = isfc(data, vectorize_isfcs=False)
      assert isfcs_r.shape == (n_subjects, n_voxels, n_voxels)
  
      # Squareform these into condensed ISFCs and ISCs
      isfcs_c, iscs_c = squareform_isfc(isfcs_r)
      assert isfcs_c.shape == (
          n_subjects,
          n_voxels * (n_voxels - 1) / 2,
      )
      assert iscs_c.shape == (n_subjects, n_voxels)
  
      # Go back the other way and check it's the same
      isfcs_new = squareform_isfc(isfcs_c, iscs_c)
      assert np.array_equal(isfcs_r, isfcs_new)
  
      # Check against ISC function
      assert np.allclose(isc(data), iscs_c, rtol=1e-03)
  
      # Check for two subjects
      isfcs_r = isfc(data[..., :2], vectorize_isfcs=False)
      assert isfcs_r.shape == (n_voxels, n_voxels)
      isfcs_c, iscs_c = squareform_isfc(isfcs_r)
      assert isfcs_c.shape == (n_voxels * (n_voxels - 1) / 2,)
      assert iscs_c.shape == (n_voxels,)
      assert np.array_equal(isfcs_r, squareform_isfc(isfcs_c, iscs_c))
  
file_path: brainiak/tests/isc/test_isc.py
imports: import numpy
  import logging
  import pytest
  from brainiak.isc import isc, isfc, bootstrap_isc, permutation_isc, squareform_isfc, timeshift_isc, phaseshift_isc
  from scipy.spatial.distance import squareform
label_desc: Use image node_id 13 for calling a global function with example usage: test_squareform_isfc() without return types